India’s low female labour force participation rate (LFPR) throughout the 21st century fell even further to 18.6 percent in 2018. In a fast-paced world where automation and artificial intelligence are being adopted by multiple organizations, the effect on female employment must be tracked and critically analysed.
Automation can be full (where a machine tends to replace manual labour) as well as partial (where instead of replacing, machines change the job in meaningful ways.) Women and men are affected differently by automation and according to a McKinsey report, it will shift the labour market drastically by 2030. As a result of this women may have a hard time coping due to various constraints faced by them. This article talks about how women must transform their skills to keep up with the changing job landscape, especially in India.
It is estimated that up to 12 million women in India could risk losing their jobs to automation by 2030. A majority of India’s female workforce is absorbed in the primary sector. Over 60 percent female jobs in the agriculture sector would lead to a 28 percent loss of jobs for women i.e approximately 4 million women involved in agriculture, fisheries and forestry risk losing their jobs followed by craft and related trade work (3 million) and warehousing (2 million).
India’s problem escalates due to the low representation of females in sectors other than agriculture, which is expected to lose a significant number of jobs-- 45 percent of total job losses compared to 26 percent for men. As a result, many women leave the labour force entirely. Despite relatively large job displacement in agriculture, men have higher representation in other sectors to redeem these losses. By 2030, the maximum gains in jobs for men would be in the medium wage bracket whereas for women it will be in the high wage category. High paying jobs for women could potentially narrow the wage gap, but this is only possible if women can make the "transition" by developing new skills.
It is also predicted that there will be jobs gained in different sectors. About 74 percent of net jobs gained in India will be in sectors such as manufacturing (11 million), accommodation and food services (2 million), retail and wholesale (1 million), and construction (3 million). The rate of automation in emerging economies like India is expected to be slower, as compared to mature economies.
Even with a slow rate of automation and an increase in jobs gained, the inequality in India's labour force persists. This is evident by the estimated addition of 23 million jobs for women compared to 91 million for men by 2030. The LFPR of India shows that females stand at a meager 18.6 percent Compared to over 50 percent for men. Yet, for upcoming sectors like manufacturing and construction, women and men both gain 1 job for every 3 displaced. The ratio of jobs gained to jobs lost tends to be similar for men and women but is not commensurate with the LFPR, which reveals a dwindling number of women.
There has been little or no progress in facilitating women to transition to sectors with higher potential, such as manufacturing and tourism. Almost three-fourths of vocational courses taken up by Indian women pertain to sectors such as textiles, healthcare, beauty, and Information Technology (IT). To have a successful movement in enabling skills in rural women, rural initiatives, and ease of mobility need to be focused upon.
As jobs are lost and gained, there will be a “transition” to different sectors, which would require a completely new skill set to be adopted. Even with a slightly larger threat of automation for men (21 percent versus 20 percent for women), advantage can be taken of this shift in the job market by developing vital skills that will be in demand due to flexibility, mobility, and ease of access. This is where women, especially those in the rural areas are cornered by various social and economic barriers.
In India, it will be crucial for women engaged in agriculture to reskill themselves, as demand for labour with less than secondary education is likely to decline. The requirement of access to technology and knowledge is unattainable for many as education rates of females in India are lower than their male counterparts. The number of women who entered the workforce at entry-level was only 25 percent of jobs from total graduates (43 percent). It is hence becoming more important for women to complete their education and gain entry into the workforce thereafter. Apart from education gaps, mobility is one of the many problems as women face the peril of physically traveling safely to their workplace and back, curtailing their movement. Women also devote a substantial amount of their time doing unpaid care work-- Estimated more than 1.1 trillion hours a year, versus less than 400 billion hours for men. Furthermore, Domestic work is also taken up largely by women, where they spend 352 minutes per day on it, 577 percent more than men (52 minutes) which leads to a "double burden” of work, i.e. working for pay and working unpaid at home.
Crossing the digital divide is imperative but difficult for a majority of the women whose jobs are under threat due to automation. In India, only 29 percent of women have access to the internet. It has the second-largest gender gap in digital inclusion within the Asia Pacific. In 2016, only 25 percent of women from rural areas and 40 percent from urban areas were internet users, and only 46 percent own a mobile phone. A survey conducted by Global Systems for Mobile Communications Association reported that 35 percent of women and 26 percent of men said they lacked internet knowledge and regarded it as a barrier. Even in higher education, globally, only 35 percent of STEM (Science, Technology, Engineering and Mathematics) students are women as they tend to study natural sciences over applied sciences. The proportion of women in tech-related jobs is also observed to be very poor, being less than 20 percent in mature economies.
India as an emerging economy must take the full responsibility of mitigating the problem of an even lower female participation rate due to automation. Digital inclusion of women cannot be ignored as global and national data both outline a disturbing future if countries are not able to support the transition of females to newer and more advanced jobs.
Conclusively, women must be given more access to technology and the internet, along with building their digital skills. This is perhaps the most important bridge to gap to cross the digital divide. Next, education of women must be emphasized and they should be encouraged to take up STEM and IT roles. This is a long-run solution, ensuring a better equipped female generation who can make the transition into AI intensive jobs.
There is also a need for safe spaces for women. This includes physical safety as well as internet safety. The UN estimates that 95 percent of aggressive behaviour and harassment in online spaces are aimed at women. A survey conducted in India discerned that cyberstalking victims aged between 18-32 were majorly female. These issues must be tackled to make it possible for women to acquire and work in new jobs within the Netscape.
Lastly, corporations must launch women-centered policies. This includes maternity leave, child care leave, daycare facilities, etc. Due to an extraordinary amount of unpaid care work performed by women, it is essential to accommodate such needs.
An example of a progressing sector is the “Gig Economy”. The gig economy provides a plethora of opportunities to women who are semi-skilled or without professional degrees. Women and men have an approximately equal gender ratio in the gig economy, and the pay gap tends to be narrower than in the formal economy. It can also facilitate flexible and remote work for women. However, lack of internet access, income insecurity, and safety need to be addressed even in the gig economy. It is a long way for India to achieve an equal female labour participation rate, and if suitable changes are not adopted promptly, it can lead to a larger gender and wage gap.
Ananya Isha Das in a Research Intern at ORF
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